KR102662229B1 - Method for detecting target object and apparatus thereof - Google Patents

Abstract

The present invention relates to a method and device for detecting a target object by a vehicle radar device. More specifically, a method for improving target object detection performance by recognizing and suppressing interference signals received by a radar device of another vehicle. and devices. In particular, one embodiment includes a signal transmitter that transmits a transmission signal for detecting a target object, a signal receiver that receives a receive signal including a target signal generated when the transmit signal is reflected by the target object, and a signal receiver that calculates frequency spectrum information of the received signal. and a signal analysis unit that extracts periodicity information to check the periodicity of the frequency spectrum information, a determination unit that determines whether the received signal contains an interference signal based on the periodicity information, and a target that extracts the target signal by suppressing the interference signal. An apparatus and method for detecting a target object including a detection unit are provided.

Description

Target object detection method and device {METHOD FOR DETECTING TARGET OBJECT AND APPARATUS THEREOF}

The present invention relates to a method and device for detecting a target object by a vehicle radar device. More specifically, a method for improving target object detection performance by recognizing and removing interference signals received by a radar device of another vehicle. and devices. .

Automotive radar refers to various types of radar devices that can be mounted on a vehicle, and is used to prevent the possibility of accidents due to poor weather conditions or driver's carelessness and to detect objects around the vehicle.

Recently, as interest in safety and driver convenience has increased, various vehicle safety and convenience technologies using such vehicle radar devices are being developed. For example, various technologies are being developed, such as smart cruise technology, automatic driving technology, and automatic emergency stop technology that detects a vehicle in front and automatically follows and drives the detected vehicle in front.

Automotive radar, which can be widely used in these technologies, can detect surrounding objects by transmitting signals and then using the signals reflected by the objects.

However, with the widespread use of automotive radars, problems with interference between radar signals are occurring. In particular, when the radar signal of the interfering vehicle is transmitted in a very short pulse compared to the radar signal of the own vehicle, the radar signal of the interfering vehicle is received in a very repetitive and periodic form within one cycle of the own vehicle's radar reception signal. Because of this, a problem arises in which it is difficult to detect the target signal of the own vehicle.

Against this background, this embodiment seeks to propose a method and device for analyzing received signals obtained from a radar device to determine whether interference signals from other radar signals exist.

In addition, this embodiment seeks to improve target object detection performance by confirming the type of interference signal through analysis of the received signal and setting target object detection parameters classified according to the type of interference signal.

An embodiment devised to solve the above-described problem includes a signal transmitting unit that transmits a transmission signal for detecting a target object, a signal receiving unit that receives a reception signal including a target signal generated when the transmission signal is reflected by the target object, and a reception unit that receives the signal. A signal analysis unit that calculates the frequency spectrum information of the signal and extracts periodicity information to check the periodicity of the frequency spectrum information, and a determination unit that determines whether the received signal contains an interference signal based on the periodicity information and removes the interference signal. A target object detection device including a target detection unit that extracts a target signal is provided.

One embodiment includes a signal transmission step of transmitting a transmission signal for detecting a target object, a signal reception step of receiving a reception signal including a target signal generated when the transmission signal is reflected by the target object, and calculating frequency spectrum information of the reception signal. A signal analysis step of extracting periodicity information to check the periodicity of the frequency spectrum information, a determination step of determining whether the received signal includes an interference signal based on the periodicity information, and a target signal of extracting the target signal by removing the interference signal. A target object detection method including a detection step is provided.

As described above, according to this embodiment, the target object detection performance can be improved by analyzing the received signal obtained from the target object detection device and efficiently removing the interference signal.

In addition, according to this embodiment, there is an effect of improving target object detection performance even in an environment where various interference signals exist by distinguishing the type of interference signal and adjusting target detection parameters accordingly.

Figure 1 is a diagram to explain the deterioration of detection performance of a target signal due to an interference signal.
FIG. 2 is a diagram illustrating the configuration of a target object detection device according to an embodiment.
Figure 3 is a diagram illustrating periodicity information extracted through fast Fourier transform according to an embodiment.
Figure 4 is a diagram illustrating a binary frequency spectrum according to an embodiment.
Figure 5 is a diagram illustrating periodicity information extracted using a binary frequency spectrum according to an embodiment.
FIG. 6 is a diagram illustrating an exemplary binary peak frequency spectrum according to an embodiment.
FIG. 7 is a diagram illustrating periodicity information extracted using a binary peak frequency spectrum according to an embodiment.
Figure 8 is a diagram illustrating periodicity information extracted through inverse fast Fourier transform according to an embodiment.
FIG. 9 is a diagram illustrating an operation for distinguishing types of interference signals according to an embodiment.
FIG. 10 is a diagram illustrating an exemplary spectrum in which peak value components are suppressed in periodicity information according to an embodiment.
FIG. 11 is a diagram illustrating a converted frequency spectrum converted after suppressing peak value components according to an embodiment.
Figure 12 is a flowchart explaining a method for detecting a target object according to an embodiment.

Hereinafter, some embodiments of the present invention will be described in detail through illustrative drawings. In describing the components of the present invention, terms such as first, second, A, B, (a), (b), etc. may be used. These terms are only used to distinguish the component from other components, and the nature, sequence, or order of the component is not limited by the term. When a component is described as being “connected,” “coupled,” or “connected” to another component, that component may be directly connected or connected to that other component, but there is another component between each component. It will be understood that elements may be “connected,” “combined,” or “connected.”

The present invention discloses a target object detection device and a target object detection method.

As automotive radar is becoming increasingly popular, various driver convenience functions using it are being developed. The Adaptive Cruise Control (ACC) function is an example of such convenience functions, and is a function that automatically controls the speed or steering of the vehicle while automatically maintaining a safe distance from the target vehicle in front.

However, in order for these functions to operate normally and provide convenience to drivers, the high reliability of a radar device that can continuously detect and track the vehicle ahead is very important. Radar devices are more reliable than other sensors such as cameras in heavy rain or fog situations where visibility is limited, but in situations where there are radar signals transmitted from various structures on the road or oncoming vehicles, various interference signals may be generated. This may cause deterioration in the performance of detecting the target object.

For example, mutual interference of FMCW (frequency modulated continuous waveform) radar appears in the form of increased noise power, which leads to failure in target detection due to the interference signal. In particular, when the interference signal from the interfering vehicle transmits a very short pulse compared to the own vehicle's radar, the interference signal is received in a very repetitive and periodic form in the time domain within one cycle of the own vehicle's radar reception signal, adversely affecting target detection. . Additionally, in a road environment with dense steel structures, the transmission signal transmitted by the vehicle may be reflected by the steel structure and received as a clutter signal, and this clutter signal is also an interference signal and has a negative effect on target detection.

In this embodiment, in order to solve this problem, a target object detection device and a target object detection method that can quickly and accurately detect the target object by detecting and removing the interference signal even in an environment where interference signals are generated due to multiple factors are described. do. In addition, this embodiment describes a method and device for providing more accurate target object detection performance by distinguishing the type of interference signal and dynamically changing and applying parameters in the signal processing process for target object detection.

Clutter, described below, refers to reflection disturbances such as echoes caused by unnecessary reflected waves generated from the ground, sea surface, raindrops, etc. in radar technology. In this specification, a clutter structure refers to an object that causes clutter, and a clutter signal refers to a signal component received by a radar by unnecessary reflected waves. Clutter signals are distinguished from general noise signals and can be received with a stronger intensity than the target signal caused by the target object, causing problems in detection of the target object. Hereinafter, the clutter structure described may mean a structure around or on the road that generates a clutter signal when a radar signal is received.

In this specification, radar signals from other vehicles or clutter signals from clutter structures are described as interference signals. In other words, interference signals can be used to include radar signals and clutter signals, and also refer to various signals that can weaken the detection performance of target signals.

Figure 1 is a diagram to explain the deterioration of detection performance of a target signal due to an interference signal.

Referring to FIG. 1, in a situation 100 where the own vehicle 110 and another vehicle 120 are driving in opposite directions, the radar transmission signal of the own vehicle 110 and the radar transmission signal of the other vehicle 120 interfere with each other. It can act as a signal. For example, a radar transmission signal from another vehicle 120 may be received as a reception signal from the own vehicle 110. When the radar transmission signal of another vehicle 120 has a shorter period on the time axis compared to the radar transmission signal of the own vehicle 110, the own vehicle 110 receives repetitive and periodic interference signals within one period. It has a negative effect on target signal detection.

Additionally, when a vehicle passes through a steel tunnel, etc., reflected signals reflected by multiple steel tunnel structures may be received as reception signals, which may have a negative impact on target detection. For example, in an environment where many steel structures with high reflectivity for transmission signals are placed at regular intervals, the transmission signals are reflected by the steel structures, generating a large number of received interference signals, which may weaken target signal detection performance.

Specifically, when an interference signal is received as included in a received signal, the frequency spectrum 150 of the received signal includes a plurality of interference signal components. Due to multiple interference signal components, it may be difficult to detect the target signal component 160 by the target object. That is, the size of the interference signal component excluding the target signal component 160 is calculated to be large, so the detection performance of the target signal component 160 may be weakened or distortion may occur.

In this embodiment, a target object detection device to solve this problem will be described.

FIG. 2 is a diagram illustrating the configuration of a target object detection device according to an embodiment.

Referring to FIG. 2, the target object detection device 200 includes a signal transmission unit 210 that transmits a transmission signal for detecting the target object. The transmission signal may refer to an RF signal having a frequency band for radar signals. The target object detection device 200 can detect a target object by transmitting a transmission signal in front or around the vehicle at a certain period or continuously.

Additionally, the target object detection device 200 includes a signal receiver 220 that receives a received signal including a target signal generated when a transmitted signal is reflected by a target object. The receiver 220 receives a reception signal that is received by a reception antenna after the above-mentioned transmission signal is reflected by a target or a surrounding object that generates various reflected waves. Additionally, the received signal may include interference signals and noise signals. The target object detection device 200 may transmit a transmission signal at a certain period or continuously and detect a target object using a reception signal that is a reflected signal of the transmission signal. The target object detection device 200 in this embodiment may be a radar device of various types using transmission and reception signals, and is not limited by the type of transmission or reception signal and the signal transmission and reception method. However, hereinafter, for convenience of explanation, the description will be made assuming the case of a 77 GHz long-range forward looking FMCW radar (e.g., a long-range FMCW radar for forward surveillance) as an example.

Additionally, the target object detection device 200 includes a signal analysis unit 230 that calculates frequency spectrum information of the received signal and extracts periodicity information to check the periodicity of the frequency spectrum information. The signal analysis unit 230 calculates frequency spectrum information of the received signal. Frequency spectrum information can be calculated through Fourier transform of the received signal. In this case, multiple interference signal components may exist, such as 150 in FIG. 1. The signal analysis unit 230 may extract periodicity information using the calculated frequency spectrum information. As an example, the signal analysis unit 230 may extract periodicity information by performing a fast Fourier transform (FFT) on the frequency spectrum information. As another example, the signal analysis unit 230 calculates binary frequency spectrum information using frequency spectrum information and a binary reference value, and extracts periodicity information by performing fast Fourier transform (FFT) on the calculated binary frequency spectrum information. You can. As another example, the signal analysis unit 230 calculates binary peak frequency spectrum information using frequency spectrum information and a binary reference value, and performs fast Fourier transform (FFT) on the calculated binary peak frequency spectrum information to generate periodicity information. can be extracted. As another example, the signal analysis unit 230 may extract periodicity information by performing an inverse fast Fourier transform (IFFT) on the frequency spectrum information. As another example, the signal analysis unit 230 may extract periodicity information by taking a log of the frequency spectrum information and then performing a fast Fourier transform. As another example, the signal analysis unit 230 may log the frequency spectrum information and then perform an inverse fast Fourier transform (IFFT) to extract periodicity information. That is, the signal analysis unit 230 can obtain the Cepstrum of the received signal and use it to check periodicity information. As another example, the signal analysis unit 230 may square the size of the frequency spectrum information and then extract periodicity information by performing fast Fourier transform or inverse fast Fourier transform (IFFT). That is, the signal analysis unit 230 can obtain the auto-correlation of the received signal and use it to check periodicity information. In addition, the signal analysis unit 230 can extract periodicity information of the frequency spectrum by changing the frequency spectrum information to another domain. A variety of methods, such as the above-described FFT, binary FFT, and IFFT, can be used to change to a different domain, and are not limited to a specific method. Hereinafter, for convenience of understanding, the description will focus on some embodiments of the above-described periodicity information extraction method. However, this is only for convenience of understanding, and each of the above-described embodiments may be performed in the same manner.

Additionally, the target object detection device 200 includes a determination unit 240 that determines whether an interference signal is included in the received signal based on periodicity information. The determination unit 240 may determine whether an interference signal exists in the received signal using the peak value component of the periodicity information. For example, if a peak value component exists in the periodicity information, the determination unit 240 may determine that the received signal includes an interference signal that generates the peak value component. Alternatively, the determination unit 240 may determine that an interference signal is included when peak value components included in the periodicity information appear at regular intervals.

Meanwhile, when the peak value component of the periodicity information is detected, the determination unit 240 may distinguish the type of interference signal included in the received signal using the band information in which the corresponding peak value component was detected. For example, if the peak value component detected in the periodicity information is detected in a band below a preset band reference value, it may be determined that the received signal contains an interference signal generated by another radar signal. Conversely, if the peak value component detected in the periodicity information is detected in a band equal to or higher than a preset band reference value, it may be determined that the corresponding received signal contains a clutter signal as an interference signal. Alternatively, the determination unit 240 may determine that a clutter signal caused by a clutter structure is included in the received signal as an interference signal when the peak value component included in the periodicity information appears at regular intervals. Accordingly, the determination unit 240 can use the periodicity information to confirm the periodic occurrence of a peak value component that is not confirmed in the frequency spectrum information and determine that the received signal includes an interference signal using the periodicity information.

Additionally, the target object detection device 200 includes a target detection unit 250 that removes interference signals and extracts target signals. If it is determined that an interference signal exists based on the periodicity information, the target detector 250 may suppress the peak value component of the periodicity information. Here, in order to suppress the peak value component of the periodicity information, the corresponding component may be deleted (remove: set to zero) or the value of the corresponding component may be changed using an interpolation method. Alternatively, the value of the corresponding suppression target component can be changed using a smoothing filter. The above-described suppression method is merely an example, and various methods of changing the peak value may be applied to suppress the peak value component of the periodicity information, and there is no limitation thereto. Thereafter, the target detection unit 250 may detect the target object by converting the periodicity information with the peak value component suppressed into frequency spectrum information. The method by which the target detection unit 250 converts periodicity information into frequency spectrum information can be performed in reverse of the method of converting frequency spectrum information into periodicity information. As an example, the target detector 250 may convert periodicity information with suppressed peak value components into a frequency spectrum by performing FFT or IFFT. As another example, the target detector 250 may IFFT the periodicity information with the peak value component suppressed and multiply it with the existing frequency spectrum to convert it into a frequency spectrum. As another example, the target detector 250 may convert the periodicity information with suppressed peak value components into a frequency spectrum by performing FFT. In addition, the target detector 250 can apply various methods to convert the domain of periodicity information into the frequency domain.

The target detection unit 250 can detect the target object using converted frequency spectrum information that is converted back to a frequency spectrum after the peak value in the periodicity information has been suppressed. In this case, since the peak value component in the periodicity information is suppressed, the peak component due to the interference signal in the frequency spectrum is significantly reduced, and detection of the target signal becomes easier. Therefore, the target detection unit 250 can easily detect the target signal through conversion frequency spectrum analysis after suppressing the peak value component of the periodicity information even in situations where it is difficult to detect the target signal using the frequency spectrum of the received signal.

In addition, the target detection unit 250 can dynamically adjust parameters for detecting the target signal using the result of the determination unit 240 distinguishing whether the interference signal is generated by another radar signal or a clutter structure. You can. For example, the reference value for target signal detection can be set in advance according to the type of interference signal, and once the type of interference signal is determined, the reference value can be applied differently depending on the corresponding interference signal. In addition, various parameters for detecting target signals can be set in advance, and the parameters can be dynamically changed depending on the type of interference signal.

Hereinafter, the target object detection device according to the above-described embodiment will be described in more detail with reference to the drawings.

Figure 3 is a diagram illustrating periodicity information extracted through fast Fourier transform according to an embodiment.

Referring to FIG. 3, the received signal received by the target object detection device may include at least one of a noise signal, an interference signal, and a target signal depending on the situation. The signal analysis unit converts the received signal into the frequency domain and calculates frequency spectrum information 300. The frequency spectrum information 300 may include all frequency components according to interference signals, noise signals, and target signals. Therefore, when an interference signal is included, multiple peak value components may be included in the frequency spectrum information 300, which makes it difficult to detect the peak value component by the target signal.

For example, in the case of FMCW radar, the method of calculating frequency spectrum information using received signals is as follows.

The signal for each channel received when the signal transmitted from the FMCW radar is reflected by L objects can be defined as follows in Equation 1.

A _k (i) is the amplitude of the signal reflected by each object. f(i) is the sum or difference of f _r (i), which is the frequency difference value caused by the distance of the object, and f _d (i), which is the frequency difference value caused by relative speed, and is expressed in Equation 2 and Equation 3, respectively. It can be obtained with f(i) can be determined as the sum or difference of f _r (i) and f _d (i) depending on the up-chirp or down-chirp of the signal.

Here, B is the bandwidth, T is the duration of the chirp, c is the speed of light, f _c is the center frequency, and R(i) and V _r (i) are the distances, respectively. and relative speed. Also, ϕ _k (i) is the phase component for each channel of each received signal.

S _k (n) is a discrete-time signal of S _k (t) and can be expressed as Equation 4.

Here, n is the discrete-time index of the received signal during a single scan, and N is the total number of samples of the received signal during a single scan.

This received signal can be expressed as Equation 5 by using short-time Fourier transform (STFT) or FFT.

Here, f is the frequency index and m is the scan index.

The magnitude response, which is the sum of the frequency domain signals for each receiving channel, can be obtained as shown in Equation 6.

As described above, the signal analysis unit can calculate frequency spectrum information using the received signal. An example of calculating frequency spectrum information has been described above, but in addition, various frequency-related response information, such as frequency response information, can be calculated. There are no restrictions on the method of calculating frequency spectrum information.

The signal analysis unit can calculate periodicity information 310 using the frequency spectrum information 300 calculated in the above manner. In these embodiments, the X-axis and Y-axis of the periodicity information are expressed as indices and sizes, respectively, and the units can be changed in various ways depending on the signal processing method for extracting the periodicity information. For example, the periodicity information 310 extracted by FFT the frequency spectrum information 300 includes a plurality of peak value components. The signal analysis unit extracts the periodicity information 310 using the frequency spectrum 300, and the determination unit determines at least one of the presence or absence of the peak value component of the periodicity information 310, the detection type of the peak value component, and the detection location of the peak value component. One can be used to check whether the received signal contains an interference signal. Alternatively, the determination unit may determine the cause of the interference signal included in the received signal (for example, the type of interference signal).

Above, the signal analysis unit explained the method of using FFT to extract periodicity information using the frequency spectrum of the received signal. Hereinafter, various methods for extracting periodicity information will be explained, focusing on drawings according to individual embodiments. It is explained as follows.

Figure 4 is a diagram illustrating a binary frequency spectrum according to an embodiment. Figure 5 is a diagram illustrating periodicity information extracted using a binary frequency spectrum according to an embodiment.

Referring to FIG. 4, the signal analysis unit may calculate frequency spectrum information 400 for the received signal. When the received signal includes an interference signal, the frequency spectrum information 400 includes multiple peak value components, making it difficult to detect the target signal component 401. To solve this problem, the signal analysis unit can calculate periodicity information using frequency spectrum information.

For example, the signal analysis unit calculates binary frequency spectrum information 410 by converting the frequency spectrum information 400 into a 0 or 1 value based on a preset binary reference value, and performs a fast Fourier transform on the binary frequency spectrum information 410. Periodicity information can also be extracted using (fast Fourier transform, FFT). Specifically, the signal analysis unit uses the frequency spectrum information 400 and a preset binary reference value to convert the frequency components above the binary reference value into 1, and converts the frequency component below the binary reference value into 0 to convert the binary frequency spectrum information 410. can be created. 410 shows an example of binarizing the frequency spectrum information 400 using a binary reference value of 10000. The signal analysis unit may extract periodicity information by FFTing the binary frequency spectrum information 410.

Referring to FIG. 5, the signal analysis unit can check periodicity information 500 obtained by FFTing the binary frequency spectrum information 410 in FIG. 4. In this case, if the frequency spectrum information (400) is binarized into 0 and 1 values, the size is constant, so it is difficult to check the peak value components (501, 502, 503, 504, 505, 506) in the periodicity information (500). easy. The target object detection device uses the peak value components (501, 502, 503, 504, 505, and 506) of the periodicity information (500) to determine whether an interference signal exists.

Meanwhile, Figure 6 is a diagram illustrating a binary peak frequency spectrum according to an embodiment. FIG. 7 is a diagram illustrating periodicity information extracted using a binary peak frequency spectrum according to an embodiment.

The signal analysis unit calculates binary peak frequency spectrum information by converting the peak component of the frequency spectrum information to a 0 or 1 value based on a preset binary reference value, and performs a fast Fourier transform on the binary peak frequency spectrum information. Periodicity information can also be extracted using FFT).

Referring to FIG. 6, the signal analysis unit may calculate the binary peak frequency spectrum information 600 by converting the frequency spectrum information 400 in FIG. 4 into 0 and 1 values depending on the binary reference value and whether there is a peak. For example, the signal analysis unit may compare the binary reference value in the frequency spectrum information 400 and convert only the peak component among components with a size greater than the binary reference value to 1. The value of the peak component with a size less than the binary reference value can be converted to 0. Additionally, all non-peak values of the frequency spectrum information 400 can be converted to 0. In this case, the number of indices with a value of 1 may be reduced compared to the binary frequency spectrum information 410 in FIG. 4. FIG. 6 shows an example in which the frequency spectrum information 400 of FIG. 4 is binarized into peak components using a binary reference value of 10000.

Referring to FIG. 7, the signal analysis unit may extract periodicity information 700 by FFTing the binary peak frequency spectrum information 600 in FIG. 6. The periodicity information 700 extracted by FFTing the binary peak frequency spectrum information 600 can confirm that the peak value components 701, 702, 703, 704, 705, and 706 occur periodically within a certain interval range. The determination unit uses whether the peak value components (701, 702, 703, 704, 705, 706) of the periodicity information (700) exist or occur periodically within a certain interval range to determine that the received signal contains an interference signal. You can judge.

Figure 8 is a diagram illustrating periodicity information extracted through inverse fast Fourier transform according to an embodiment.

The signal analysis unit may extract periodicity information by performing inverse fast Fourier transform (IFFT) on the frequency spectrum information.

Referring to FIG. 8, the signal analysis unit may extract periodicity information 800 by IFFTing the frequency spectrum information. For example, the signal analysis unit can extract the periodicity information 800 by FFTing the received signal and IFFTing the frequency spectrum information from which the magnitude response is obtained to obtain the magnitude response. In this case as well, it can be seen that peak value components (801, 802, 803, 804, 805, 806) are extracted from the periodicity information 800 and appear periodically within a certain interval range.

As described above, the signal analysis unit can extract periodicity information using various signal processing methods based on the frequency spectrum information of the received signal.

The target object detection device in this embodiment can determine whether an interference signal exists based on periodicity information. For this purpose, the determination unit may use the peak value component of the periodicity information.

For example, if the periodicity information contains a peak value component that exceeds a preset reference value, the determination unit may determine that the received signal contains an interference signal. Alternatively, the determination unit may determine that an interference signal is included when a peak value component exceeding a preset reference value is periodically detected in the periodicity information at regular intervals.

FIG. 9 is a diagram illustrating an operation for distinguishing types of interference signals according to an embodiment.

If necessary, the determination unit may determine the type of interference signal using the peak value component extracted from the periodicity information. For example, the determination unit may distinguish the type of interference signal based on the band information in which the peak value component of the periodicity information is detected. Alternatively, the determination unit may distinguish the type of interference signal by using whether the peak value component of the periodicity information is detected periodically within a preset certain interval range.

Referring to FIG. 9, when the peak value component of the periodicity information 900 extracted by the signal analysis unit is detected below the preset band reference value 905, the interference signal included in the corresponding received signal is transmitted by another radar. It can be determined that it was caused by a signal. In contrast, when the peak value component of the periodicity information 910 extracted by the signal analysis unit is detected above the preset band reference value 905, the interference signal included in the corresponding received signal is generated by the clutter structure. It can be judged that That is, the determination unit can distinguish the type of interference signal based on the location where the peak value component of the periodicity information occurs.

Meanwhile, the determination unit may determine that an interference signal due to a clutter structure exists when the peak value component of the periodicity information occurs periodically within a certain interval range. For example, when periodicity information is extracted, the determination unit may determine whether a clutter signal exists by checking whether the peak value component in the extracted periodicity information occurs within a certain interval range. That is, if the peak value component of the periodicity information exists within a certain interval range, it can be determined that a clutter signal is included in the received signal, and an environment in which a clutter structure exists can be determined. On the contrary, if there is no peak value component in the periodicity information that appears relatively large compared to surrounding values, or does not exist periodically within a certain interval range, it can be determined that the interference signal generated by the clutter signal does not exist. You can.

As an example, the periodicity information may include a peak value component that occurs periodically within a certain interval range, and if there is a peak value component that occurs periodically, it may be determined that a clutter signal is included in the received signal. there is. However, since the peak value component in the periodicity information may not occur at the same interval, it can be determined to have occurred periodically if the peak value component exists within a preset certain interval range. The peak value in the periodicity information can be extracted by extracting only peaks that exceed a preset reference value, or by checking the presence of a peak that appears larger than a certain size by comparing it with the average of surrounding size values. That is, the peak value exceeding the preset reference value can be extracted as the peak value for periodicity confirmation, and it can be determined whether the peak value occurs periodically. Alternatively, the size of each peak value may be compared with the average of surrounding peak values to extract a peak value having a size difference greater than a preset value to determine whether the corresponding peak value occurs periodically.

Since the periodicity information 900 and 910 described above is calculated in a left-right symmetrical form based on the index, the determination unit can determine the type of the interference signal based on only a part of the symmetrical form.

As described above, the target object detection device extracts periodicity information in various ways using the frequency spectrum information of the received signal, and uses the peak value component of the extracted periodicity information to determine whether an interference signal exists or the type of the interference signal. You can check information about.

FIG. 10 is a diagram illustrating an exemplary spectrum in which peak value components are suppressed in periodicity information according to an embodiment.

The target detection unit of this embodiment suppresses the peak value component of the periodicity information that is greater than a preset peak reference value, and converts the periodicity information with the suppressed peak value component into converted frequency spectrum information to extract the target signal reflected by the target object. .

Referring to FIG. 10, the target detector may suppress peak value components that occur periodically in the periodicity information and calculate periodicity information 1000 in which the peak value components are suppressed. The target detector may change the selected peak value to 0 to check the periodicity in the periodicity information and calculate periodicity information 1000 in which the peak value component is suppressed. Alternatively, the target detector may suppress the peak value component by changing the selected peak value to the size of the surrounding index to check the periodicity, or changing it to the average size of the surrounding index. In FIG. 10, the peak value component of the periodicity information 310 shown in FIG. 3 was converted to 0, and periodicity information 1000 with the peak value component suppressed was calculated. In this way, the target detector can suppress the frequency component generated by the interference signal by suppressing the peak value component in the periodicity information.

FIG. 11 is a diagram illustrating a converted frequency spectrum converted after suppressing peak value components according to an embodiment.

Referring to FIG. 11, the target detector may suppress the peak value component in the periodicity information and then convert the periodicity information into converted frequency spectrum information 1100 to extract the target signal component 1110 caused by the target object. In this case, the method of converting the periodicity information with suppressed peak value components into a converted frequency spectrum may vary depending on the method of extracting the periodicity information.

For example, when periodicity information is extracted by performing FFT on the frequency spectrum information, the target detector may perform IFFT on the periodicity information with suppressed peak value components to calculate converted frequency spectrum information 1100. In this case, the converted frequency spectrum information is different from the frequency spectrum information calculated using the received signal because the peak value component of the periodicity information is suppressed. In other words, there was a problem in that the target signal in the initial frequency spectrum information was difficult to detect due to a large number of clutter signals. However, in the converted frequency spectrum information 1100, it can be confirmed that detection of the peak 1110 of the target signal becomes easier due to the peak value component suppressed in the periodicity information. In this way, the present invention provides the effect of making detection of the target signal easier when an interference signal exists.

As another example, when periodicity information is extracted using binary frequency spectrum information, the target detector performs IFFT on the periodicity information with suppressed peak value components and then multiplies (weights) the initial frequency spectrum information to generate converted frequency spectrum information (1100). can be calculated. Specifically, the target detector may suppress the peak value component from periodicity information extracted using binary frequency spectrum information and perform IFFT using the periodicity information with the peak value component suppressed. Thereafter, in order to compensate for the binary value, the converted frequency spectrum information 1100 can be calculated by multiplying the initial frequency spectrum generated using the received signal by the spectrum on which IFFT was performed. The peak 1110 of the target signal is more clearly detected in the converted frequency spectrum information 1100.

As another example, when periodicity information is extracted using binary peak frequency spectrum information, the target detector performs IFFT on the periodicity information with suppressed peak value components and then multiplies (weights) the initial frequency spectrum information to generate converted frequency spectrum information ( 1100) can be calculated. As in the case of using the binary frequency spectrum described above, the target detector can suppress the peak value component from the periodicity information extracted using the binary peak frequency spectrum information and perform IFFT using the periodicity information with the peak value component suppressed. there is. Thereafter, in order to compensate for the binary value, the converted frequency spectrum information 1100 can be calculated by multiplying the initial frequency spectrum generated using the received signal by the spectrum on which IFFT was performed.

As another example, when periodicity information is extracted by performing IFFT on the frequency spectrum information, the target detector may perform FFT or IFFT on the periodicity information with suppressed peak value components to calculate converted frequency spectrum information 1100. Specifically, the target detector may suppress the peak value component from the periodicity information extracted by IFFTing the frequency spectrum information, and perform FFT or IFFT using the periodicity information with the peak value component suppressed. The target detector can detect the target object using the target signal peak 1110 in the converted frequency spectrum information 1100 calculated through this process.

As described above, the target detector can detect the target signal more easily than the initial frequency spectrum by suppressing the peak value component that occurs periodically in the periodicity information and converting it to the frequency domain. In other words, the target signal can be easily detected even when a clutter signal is included.

Meanwhile, the target detector may detect the target signal using initial frequency spectrum information or converted frequency spectrum information and a detection threshold. The target detector may use detection threshold information to detect a target signal from a noise signal, etc. In other words, by setting a detection threshold, it is possible to detect a target signal rather than noise only when the signal strength for each frequency exceeds the detection threshold.

However, when an interference signal exists as in the present invention and the target signal is detected to be smaller than the interference signal, it may be difficult to detect the target object. If it is determined that an interference signal exists, the target detector may detect the target object by adjusting the detection threshold so that the target signal is detected. The detection threshold in the present invention may be fixed, may be a value that changes by setting, or may be a value dynamically calculated in consideration of the intensity of surrounding frequencies, etc.

The target detection unit can correct the detection threshold and detect the final target object using an adaptive algorithm that detects the target. For example, an adaptive algorithm for detecting a target may include Constant false alarm rate (CFAR), and in addition, target objects can be detected in response to background noise such as noise, clutter, and interference from received signals. A variety of algorithms can be used.

If it is determined that an interference signal exists, the target detection unit of the present invention may correct the detection threshold calculation parameter so that the detection threshold is lowered when calculating the detection threshold for detecting the target object. Additionally, the detection threshold calculation parameters can be configured differently depending on the type of interference signal.

The existence of an interference signal is confirmed according to the determination result of the above-described determination unit, and if it is confirmed that the interference signal is not present, the target signal is detected using an existing preset detection threshold. If it is confirmed that an interference signal exists, parameter correction to adjust the detection threshold can be performed. Thereafter, the target detector may calculate a detection threshold using the corrected parameters. The detection threshold is used to detect a target signal when the target signal is received at an intensity greater than the detection threshold for noise removal, etc., and can be calculated using various algorithms. For example, in the CFAR algorithm, which determines the detection threshold using intensity information of surrounding frequencies, the detection threshold can be lowered by correcting the parameter for determining the detection threshold to a preset value. Through this, the target signal can be detected even if a strong interference signal is received.

Meanwhile, the target detector may detect a peak signal exceeding the threshold using the determined detection threshold. In this case, the detection threshold may be lower than the target signal, and therefore, some of the target signal and interference signal may be detected.

The target detection unit may detect the final target object using one or more detected peak signals. For example, if the target object is a moving object such as the vehicle in front and the interference signal is a clutter signal, the clutter signal is generated by a steel tunnel or the like and is a stationary object. Therefore, the target object, which is the final moving object, can be detected by going through an algorithm such as filtering the detected peak signal. As another example, the target object is an object moving in the same direction as the host vehicle, and if the interference signal is a signal generated by another radar, the interference signal is in the opposite direction to the moving direction of the target object, so a filtering algorithm using this is used. Target objects can also be detected.

Below, the target object detection method according to an embodiment of the present invention described with reference to FIGS. 1 to 11 will be briefly described again.

Figure 12 is a flowchart explaining a method for detecting a target object according to an embodiment.

A target object detection method according to an embodiment includes a signal transmission step of transmitting a transmission signal for detecting a target object, a signal reception step of receiving a reception signal including a target signal generated when the transmission signal is reflected by the target object, and a reception signal. A signal analysis step of calculating frequency spectrum information and extracting periodicity information to check the periodicity of the frequency spectrum information; a determination step of determining whether an interference signal is included in the received signal based on the periodicity information; and removing the interference signal. It includes a target detection step of extracting the target signal.

Referring to FIG. 12, the target object detection method includes a signal transmission step of transmitting a transmission signal for detecting the target object (S1200). The transmission signal may refer to an RF signal having a frequency band for radar signals.

In addition, the target object detection method includes a signal reception step of receiving a received signal including a target signal generated when the transmitted signal is reflected by the target object (S1210). In the reception step, the above-mentioned transmission signal is reflected by the target or surrounding objects that generate various reflected waves and receives a reception signal received by a reception antenna. Additionally, the received signal may include interference signals and noise signals.

Additionally, the target object detection method includes a signal analysis step of calculating frequency spectrum information of the received signal and extracting periodicity information to check the periodicity of the frequency spectrum information (S1220). The signal analysis step calculates the frequency spectrum information of the received signal. Frequency spectrum information can be calculated through Fourier transform of the received signal. In the signal analysis step, periodicity information can be extracted using the calculated frequency spectrum information. For example, the signal analysis step may extract periodicity information by performing fast Fourier transform on the frequency spectrum information. As another example, the signal analysis step may calculate binary frequency spectrum information using frequency spectrum information and a binary reference value, and extract periodicity information by performing fast Fourier transform on the calculated binary frequency spectrum information. As another example, the signal analysis step may calculate binary peak frequency spectrum information using frequency spectrum information and a binary reference value, and extract periodicity information by performing fast Fourier transform on the calculated binary peak frequency spectrum information. As another example, the signal analysis step may extract periodicity information by performing inverse fast Fourier transform on the frequency spectrum information. As another example, the signal analysis step can extract periodicity information by taking the logarithm of the frequency spectrum information and then performing fast Fourier transformation. In other words, the signal analysis step can obtain the Cepstrum of the received signal and use it to check periodicity information.

Additionally, the target object detection method includes a determination step of determining whether an interference signal is included in the received signal based on periodicity information (S1230). The determination step can determine whether an interference signal exists in the received signal using the peak value component of the periodicity information. For example, in the determination step, if a peak value component exists in the periodicity information, it may be determined that the received signal includes an interference signal that generates the peak value component. Alternatively, the determination step may determine that an interference signal is included when the peak value component included in the periodicity information appears at regular intervals.

Meanwhile, in the determination step, when the peak value component of the periodicity information is detected, the type of interference signal included in the received signal may be distinguished using the band information in which the corresponding peak value component was detected. For example, if the peak value component detected in the periodicity information is detected in a band below a preset band reference value, it may be determined that the received signal contains an interference signal generated by another radar signal. Conversely, if the peak value component detected in the periodicity information is detected in a band equal to or higher than a preset band reference value, it may be determined that the corresponding received signal contains a clutter signal as an interference signal. Alternatively, the determination step may determine that a clutter signal caused by a clutter structure is included in the received signal as an interference signal when the peak value component included in the periodicity information appears at regular intervals.

Additionally, the target object detection method includes a target detection step of extracting the target signal by removing the interference signal (S1240). In the target detection step, when it is determined that an interference signal exists based on the periodicity information, the peak value component of the periodicity information may be suppressed. Thereafter, in the target detection step, the periodicity information with the peak value component suppressed can be converted into converted frequency spectrum information to detect the target object. As described above, the method of converting periodicity information into converted frequency spectrum information in the target detection step can be performed in reverse of the method of converting frequency spectrum information into periodicity information.

In the target detection step, the target object can be detected using converted frequency spectrum information that is converted back to a frequency spectrum after the peak value component is suppressed in the periodicity information. In this case, since the peak value component in the periodicity information is suppressed, the peak component due to the interference signal in the frequency spectrum is significantly reduced, and detection of the target signal becomes easier.

Additionally, in the target detection step, parameters for detecting the target signal can be dynamically adjusted using the result of distinguishing whether the interference signal is generated by another radar signal or a clutter structure in the determination step. For example, the threshold reference value for target signal detection may be set in advance according to the type of interference signal, and once the type of interference signal is determined, the threshold reference value may be applied differently depending on the corresponding interference signal. In addition, various parameters for detecting target signals can be set in advance, and the parameters can be dynamically changed depending on the type of interference signal.

As described above, according to this embodiment, the target object detection performance can be improved by analyzing the received signal obtained from the target object detection device and efficiently removing the interference signal. In addition, according to this embodiment, there is an effect of improving target object detection performance even in an environment where various interference signals exist by distinguishing the type of interference signal and adjusting target detection parameters accordingly.

In the above, even though all the components constituting the embodiment of the present invention have been described as being combined or operated in combination, the present invention is not necessarily limited to this embodiment. That is, as long as it is within the scope of the purpose of the present invention, all of the components may be operated by selectively combining one or more of them. The above description is merely an illustrative explanation of the technical idea of the present invention, and various modifications and variations will be possible to those skilled in the art without departing from the essential characteristics of the present invention. The scope of protection of the present invention shall be interpreted in accordance with the claims below, and all technical ideas within the equivalent scope shall be construed as being included in the scope of rights of the present invention.

Claims (18)

A signal transmitting unit that transmits a transmission signal for detecting a target object;
a signal receiver that receives a reception signal including a target signal generated when the transmission signal is reflected by the target object;
a signal analysis unit that calculates frequency spectrum information of the received signal and extracts periodicity information to check periodicity of the frequency spectrum information;
a determination unit that determines whether the received signal includes an interference signal based on the periodicity information; and
A target detection unit that extracts the target signal by suppressing the interference signal,
The signal analysis unit,
Calculate binary frequency spectrum information by converting the frequency spectrum information to a 0 or 1 value based on a preset binary reference value, and extract the periodicity information by performing a fast Fourier transform (FFT) on the binary frequency spectrum information. or
The peak component of the frequency spectrum information is converted to a 0 or 1 value based on a preset binary reference value to calculate binary peak frequency spectrum information, and the binary peak frequency spectrum information is subjected to fast Fourier transform (FFT). ) to extract the periodicity information, or
Converting the frequency spectrum information to a log scale, and extracting the periodicity information by performing fast Fourier transform (FFT) or inverse fast Fourier transform (IFFT) on the frequency spectrum information converted to log scale. Target object detection device. According to claim 1,
The signal analysis unit,
A target object detection device, characterized in that the periodicity information is extracted by performing fast Fourier transform (FFT) or inverse fast Fourier transform (IFFT) on the frequency spectrum information. delete delete delete delete According to claim 1,
The judgment department,
A target object detection device characterized in that the existence of the interference signal is determined using a peak value component of the periodicity information. According to claim 1,
The judgment department,
A target object detection device characterized in that the type of interference signal included in the received signal is distinguished using band information in which the peak value component of the periodicity information is detected. According to claim 8,
The judgment department,
If the peak value component of the periodicity information is detected below a preset band reference value, it is determined that the interference signal is generated by a radar,
A target object detection device characterized in that, when the peak value component of the periodicity information is detected above a preset band reference value, it is determined that the interference signal is generated by a clutter structure. According to claim 1,
The target detection unit,
A target object detection device, characterized in that the target signal is extracted by suppressing a peak value component greater than a preset peak reference value from the periodicity information and converting the periodicity information with the suppressed peak value component into converted frequency spectrum information. According to claim 1,
The target detection unit,
When the difference between the first peak value and peak values located before and after the first peak value based on the first peak value included in the periodicity information is greater than or equal to a reference value, the first peak value component is suppressed, and the periodicity A target object detection device that converts information into converted frequency spectrum information and extracts a target signal reflected by the target object. According to claim 1,
The commercial target detection unit,
A target object detection device characterized in that parameters for detecting the target signal are separately applied according to the type of the interference signal. A signal transmission step of transmitting a transmission signal for detecting a target object;
A signal receiving step of receiving a received signal including a target signal generated when the transmitted signal is reflected by the target object;
A signal analysis step of calculating frequency spectrum information of the received signal and extracting periodicity information to confirm periodicity of the frequency spectrum information;
A determination step of determining whether an interference signal is included in the received signal based on the periodicity information; and
A target detection step of extracting the target signal by suppressing the interference signal,
The signal analysis step is,
Calculate binary frequency spectrum information by converting the frequency spectrum information to a 0 or 1 value based on a preset binary reference value, and extract the periodicity information by performing a fast Fourier transform (FFT) on the binary frequency spectrum information. or
The peak component of the frequency spectrum information is converted to a 0 or 1 value based on a preset binary reference value to calculate binary peak frequency spectrum information, and the binary peak frequency spectrum information is subjected to fast Fourier transform (FFT). ) to extract the periodicity information, or
Converting the frequency spectrum information to log scale, and extracting the periodicity information by fast Fourier transform (FFT) or inverse fast Fourier transform (IFFT) on the frequency spectrum information converted to log scale. Target object detection method. delete According to claim 13,
The judgment step is,
A target object detection method characterized by determining whether the interference signal exists using a peak value component of the periodicity information. According to claim 13,
The judgment step is,
A target object detection method characterized by distinguishing the type of interference signal included in the received signal using band information in which the peak value component of the periodicity information is detected. According to claim 13,
The target detection step is,
A method for detecting a target object, characterized in that the target signal is extracted by suppressing a peak value component greater than a preset peak reference value from the periodicity information and converting the periodicity information with the suppressed peak value component into converted frequency spectrum information. According to claim 13,
The commercial target detection step is,
A target object detection method characterized in that parameters for detecting the target signal are separately applied according to the type of the interference signal.

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